An in memory database platform is deployable as an on premise appliance, or as a remote server, sometimes referred to as being in the cloud. It is a platform that is best suited for performing real-time analytics, and developing and deploying real-time applications. At the core of this real-time data platform is an in memory database which is fundamentally different than common database engines where data is stored in slower but cheaper storage devices such as disk drive devices.
Database management systems on the market are typically either good at transactional workloads, or analytical workloads, but not both. When transactional database management systems are used for analytical workloads, they require separating workloads into different databases such as OLAP, Online Analytical Processing and OLTP, Online Transaction Processing. Data from transactional systems have to be transformed for reporting, and loaded into a reporting database. The reporting database still requires significant effort in creating and maintaining tuning structures such as aggregates and indexes to provide even moderate performance. Further, lagging performance of such systems reduces abilities of systems to monitor organizational performance for purposes of providing notices upon occurrences of significant events that may be reflected in stored data. This lagging system performance also is a confound to timely forecasting and generating and maintain plans based on complex organizational structures, rules, policies, and markets.